Could Solana securities lawsuit spark massive crypto delistings?

cryptodailyPublicado em 2022-07-08Última atualização em 2022-07-08

Resumo

A class action lawsuit has been filed against Solana Labs and its CEO Anatoly Yakovenko for allegedly breaking securities law.

A class action lawsuit has been filed against Solana Labs and its CEO Anatoly Yakovenko for allegedly breaking securities law. The implications for other similar cryptocurrencies could be huge, as exchanges are forced to delist them.
The lawsuit is being brought against defendants Solana Labs, CEO Yakovenko, the Solana Foundation, venture capital firm Multicoin Capital, its CEO Kyle Samani, and trading platform FalconX.
The lawsuit was filed by the plaintiff Mark Young, together with Roche Freedman LLP and Sneider Wallace Cottrell Konecky. The suit is on behalf of all Solana investors who bought the SOL token from March 24 2020, to the present time.
According to a Forbes article on the subject:
“Defendants made enormous profits through the sale of SOL securities to retail investors in the United States in violation of the registration provisions of federal and state securities laws, and the investors have suffered enormous losses,”
The lawsuit describes Solana as being a “highly centralised cryptocurrency” and stated that the defendants in the suit “determined who would receive SOL securities and under what conditions.”
One of the main defences employed by blockchain projects is their decentralised nature, but it could be imagined that Solana would have a hard time proving this given that it has been accused of being too centralised many times by detractors.
Implications for Solana and other similar projects could be disastrous for the crypto sector. Ripple is facing its own lawsuit battle with the SEC and its XRP token was delisted from Coinbase, Kraken, and other exchanges even before a verdict has been reached as to whether the token is a security or not.
Delistings and heavy fines could really take a heavy toll on crypto, and given that the sector is still deep in a bear market, any kind of rally and recovery could be negated, halting crypto in its tracks and sending it back down again, perhaps destroying some of these projects for ever.
Opinion
Some might say that many of the crypto projects that are making fantastic innovations, especially in the world of finance, needed to start how they did in order to raise money for their development.
This will certainly cut no ice with the enforcement agencies, whose raison d’etre is to apply many decades old securities laws to these innovators.
However, it has to be acknowledged that the technology that many crypto projects are developing can cause immense change for good. Hestor Pierce’s safe harbour proposal may well have been what was needed in this impasse, but once again, enforcement agencies will probably get their way.

Leituras Relacionadas

How to Do Research Well: Deliberately Practice the Real Skills That Matter

No one truly teaches you how to do research. You're often given a desk, a pre-selected problem, and vague instructions to "create something new." Consequently, many people reverse-engineer the job based on visible outputs—papers, posts, announcements—learning only how to *appear* like a researcher rather than how to *become* one. True research capability is built from stacking small, trainable skills, nearly all of which can be developed through deliberate practice. **Pick Your Own Problem:** Most researchers absorb problems from advisors or trends, lacking the underlying reasoning. Choosing a problem you genuinely care about, as John Schulman advises, leads to original work. Develop "taste" like a muscle: predict experiment outcomes, guess paper results from methods, and track which findings remain important over time. **Upgrade Your Inputs:** Relying on shared reading lists (arXiv hot lists, filtered group chats) leads to unoriginal conclusions. Undervalued old literature often holds crucial insights (e.g., MoE, LSTM, backpropagation). Richard Sutton's "The Bitter Lesson" or Claude Shannon's 1952 talk on creative thinking are more predictive than lengthy modern surveys. Breadth matters as much as depth: draw from neuroscience, mechanism design, hardware knowledge, and honest statistics. Read papers directly, especially appendices and limitations sections. **Write Everything Down:** As Paul Graham noted, writing exposes flaws in seemingly mature ideas. Writing is the cheapest defense against self-deception. Following Feynman's principle, Darwin programmatically wrote down facts contradicting his theory to combat memory bias. Maintain a detailed log of hypotheses, setups, predictions, results, and updated understandings. Reviewing past logs fosters essential humility.

marsbitHá 12m

How to Do Research Well: Deliberately Practice the Real Skills That Matter

marsbitHá 12m

Following US Ban on Fable 5, Zhipu AI's Stock Soars 47%

On June 15th, shares of Zhipu AI surged dramatically on the Hong Kong stock market, peaking at a 47.6% gain before closing 32.82% higher. This sharp increase was directly triggered by two recent industry events. On June 12th, Anthropic announced it was suspending global access to its latest flagship models, Claude Fable 5 and Claude Mythos 5, to comply with a U.S. government export control order. The next day, Zhipu AI announced it would open access to its latest open-source flagship model, GLM-5.2, under the permissive MIT license. The Anthropic incident highlighted a critical issue beyond raw model capability: the risk of sudden, unpredictable loss of access to advanced AI models, especially for developers and enterprises deeply integrated with them. This has shifted industry and market focus toward factors like stability, sustainable access, and controllability. Zhipu's move, promoting "frontier intelligence for all," positions its openly available model as a reliable and accessible alternative. The GLM-5.2 model emphasizes "Long Horizon Task" capabilities with a 1M context window, targeting complex, multi-step coding and engineering workflows where maintaining context is crucial. Analysts note this event exposes the risk of dependency on closed-source models subject to single jurisdictional controls, potentially accelerating a shift toward domestic base models and localized deployments. The market's reaction signals a new valuation dimension in AI: providers who can offer stable, long-term, and sustainably accessible AI capabilities are gaining strategic importance.

marsbitHá 36m

Following US Ban on Fable 5, Zhipu AI's Stock Soars 47%

marsbitHá 36m

Fully Entering the AI Era: Alipay Bets on Conversation, WeChat Holds Fast to Social

In May 2026, Alipay announced over 300 million AI payment transactions. Shortly after, WeChat opened its mini-programs for AI integration, sparking controversy by requiring developer source code access. This highlights their diverging approaches to AI integration. Alipay is testing "Project Treasure," an optional AI-native interface replacing traditional app grids with a conversational window. Users can command complex tasks (e.g., "book a ride and order coffee") handled end-to-end by AI. This shift follows an abandoned standalone AI app, focusing instead on enhancing its existing user base. For unmodified mini-programs, Alipay's AI uses "screen-reading" to simulate user interactions, bypassing the need for developer overhaul. It also introduced "Token Pay" for micro-transactions and "AI Wallets" for autonomous agent spending. WeChat, prioritizing its core social function, is taking an embedded approach. Its AI agent will operate within existing contexts like group chats and official accounts, assisting without a separate interface. To enable this, WeChat offers developers two paths: granting source code access for direct AI control ("Automatic Mode") or manually encapsulating services into standardized "Skills." Both place significant burden on developers. Key differences emerge in handling legacy services: WeChat demands developer cooperation (code or labor), while Alipay's screen-reading offers immediate, if potentially less stable, compatibility. Alipay's 3 billion AI transactions demonstrate user acceptance of AI-driven commercial actions. The divergent strategies may reshape mini-program ecosystems—Alipay passively "AI-fying" services, WeChat potentially favoring resource-rich developers—and set competing technical standards. Ultimately, the competition centers on where users entrust the command to "help me get things done."

marsbitHá 36m

Fully Entering the AI Era: Alipay Bets on Conversation, WeChat Holds Fast to Social

marsbitHá 36m

Trading

Spot
Futuros
活动图片